Social community based blog search framework
- Authors
- Jeong, O.-R.; Oh, J.
- Issue Date
- 2012
- Publisher
- Springer Verlag
- Keywords
- Blog search engine; Collective intelligence; Q& A information; Social community
- Citation
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.7240 LNCS, pp.130 - 141
- Journal Title
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- Volume
- 7240 LNCS
- Start Page
- 130
- End Page
- 141
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/16690
- ISSN
- 0302-9743
- Abstract
- This study proposes a blog search framework which enables a more in-depth search on a given topic by extracting the collective intelligence features in social community sites and through the query extension using these features. The characteristics of blog contents is that it has a lot of information made up of user experience and trusted more by most users than the contents gained by general search. The proposed framework extends the query using the answer information related to the query which the user wishes to search and gets applied to the blog search on this basis. The information gained from various types of social community sites could be considered as one form of collective intelligence while this has been applied to the blog search. The framework proposed in this paper utilizes the important Q&A information of social community to let the user gain more reliable and useful search results. © Springer-Verlag Berlin Heidelberg 2012.
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